thumbnail

Topic

Technologies and technical equipment for agriculture and food industry

Volume

Volume 69 / No. 1 / 2023

Pages : 177-184

Metrics

Volume viewed 0 times

Volume downloaded 0 times

EXPERIMENT AND ANALYSIS OF MECHANIZED PICKING OF CAMELLIA OLEIFERA FRUIT BASED ON ENERGY UTILIZATION RATE

基于能量利用率的油茶果机械化采摘试验与分析

DOI : https://doi.org/10.35633/inmateh-69-16

Authors

(*) Delin WU

School of Engineering, Anhui Agricultural University, Hefei, China

Enlong ZHAO

School of Engineering, Anhui Agricultural University, Hefei, China

Dong FANG

School of Engineering, Anhui Agricultural University, Hefei, China

Yilin LIU

School of Engineering, Anhui Agricultural University, Hefei, China

Shunli WANG

School of Engineering, Anhui Agricultural University, Hefei, China

Cheng WU

School of Engineering, Anhui Agricultural University, Hefei, China

Feng GUO

School of Engineering, Anhui Agricultural University, Hefei, China

(*) Corresponding authors:

Abstract

In order to use the resonance principle for vibratory picking of Camellia oleifera fruit, the frequency sweep tests were carried out on the fruiting branches of Camellia oleifera trees. The results showed that the acceleration response of fruit-bearing branches had good consistency. The use of fruit removal rate alone to evaluate the picking effect is not reliable, and the introduction of energy utilization to evaluate the vibration picking effect is significant. The best results were a vibration frequency of 8 Hz and an excitation time of 10 s. The fruit removal rate was 88.12% and the energy utilization rate was 36.72%. Compared with the traditional fruit shedding rate, the application of energy utilization rate to evaluate the picking effect can improve the reliability of the results and reduce the energy loss.

Abstract in Chinese

为了利用共振原理对油茶果进行振动采摘,对油茶树挂果枝条进行扫频试验。结果表明:挂果枝条的加速度响应具有较好的一致性。仅使用果实去除率不能准确评价采摘效果,引入能量利用率评价振动采摘效果是显著的。采用8Hz振动频率和10s激振时间的振动采摘效果最佳,此时油茶果实去除率为88.12%,能量利用率为36.72%。与传统果实脱落率相比,应用能量利用率评价采摘效果可以提高结果的可靠性,同时降低能量的损失。

Indexed in

Clarivate Analytics.
 Emerging Sources Citation Index
Scopus/Elsevier
Google Scholar
Crossref
Road